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Jobs

Introduced by Uri Shalit et al. in Estimating individual treatment effect: generalization bounds and algorithms13 Jun 2016 archive 2025-07-28

The Jobs dataset by LaLonde [36] is a widely used benchmark in the causal inference community, where the treatment is job training and the outcomes are income and employment status after training. The dataset includes 8 covariates such as age, education, and previous earnings. Our goal is to predict unemployment, using the feature set of Dehejia and Wahba [37]. Following Shalit et al. [8], we combined the LaLonde experimental sample (297 treated, 425 control) with the PSID comparison group (2490 control).

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Causal Inference Jobs BCAUSS Average Treatment Effect on the Treated Error 0.05 Learning end-to-end patient representations through... anthem-ai/bcauss 5 Compare

Papers archive 2025-07-28

4 shown of 4 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 56. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

Dataset loaders archive 2025-07-28

1 loader as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • Jobs

1 variant name, as the archive lists them.

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